5. 问题描述 _ 研究现状分析 [10] Wing W.Y.NG, Daniel S.YEUNG, De-Feng Wang, Eric C.C.TSANG, and Xi-Zhao Wang, Localized generalization error and its application to RBFNN training. Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, 18-21 August 2005. 基于 LGEM ,利用最大化覆盖面积 ( MC 2 SG )的方法选择网络结构 (隐层中心) [9] Wing W.Y.Ng, Daniel S.Yeung, Ian Cloete, Quantitative study on effect of center selection to RBFNN classification performance, IEEE International Conference on Systems, Man and Cybernetics, Vol.4, pp.3692-3697, 2004. (输入和权重的敏感性) [8] D.Shi, D.S.Yeung, J.Gao, Sensitivity analysis applied to the construction of radial basis function networks, Neural Networks 18 (2005) (7), pp. 951-957. (中心敏感性) 利用敏感性度量选择隐层中心 [7] K.Z.Mao, RBF neural network center selection based on fisher ratio class separability measure, IEEE transactions on neural networks, Vol.13, No.5, Sep. 2002 利用 Fisher ratio 度量来选择隐层中心 [6] J.Barry Gomm, Member, IEEE, Ding Li Yu, Selecting radial basis function network centers with recursive orthogonal least squares training, IEEE Transactions on Neural Networks, Vol.11, No.2, Mar. 2000. 利用正交最小二乘方法选择隐层中心